Traffic-ELT / Migration

Traffic-ELT / Migration

Cross-platform Traffic Data Pipeline & Migration

July 2022

Overview

I designed and implemented a data engineering solution that not only processes traffic data but also enables seamless migration between database technologies. This dual-purpose system provides robust Extract, Load, Transform (ELT) capabilities alongside database migration functionality, allowing organizations to maintain data consistency while transitioning between PostgreSQL and MySQL environments.

Key Features

  • Bidirectional Database Migration: Engineered automated workflows to synchronize data between PostgreSQL and MySQL databases with integrity verification
  • Cross-Platform Analytics: Integrated both Redash and Apache Superset for flexible visualization options across different database backends
  • Automated Data Ingestion: Efficiently processes raw traffic sensor data with custom parsing logic to handle semi-structured formats
  • Modular Transformation Layer: Implements dbt models for creating specialized data views (vehicle types, speed thresholds) with built-in data quality tests
  • Database-Agnostic Transformations: dbt models designed to work across different database engines with minimal adaptation
  • Multi-Environment Orchestration: Leverages Apache Airflow for reliable scheduling and monitoring of both processing and migration workflows

Technical Implementation

  • Database Migration Strategy: Implemented incremental and full migration patterns with checksum validation to ensure data integrity
  • Containerized Architecture: Complete Docker-based deployment with separate services for PostgreSQL, MySQL, Airflow, dbt, Redash, and Apache Superset
  • Schema Synchronization: Automated schema detection and creation across database platforms
  • Parallel Processing: Optimized migration jobs for large datasets through parallel execution paths
  • Configuration Management: Externalized database connection parameters and migration settings for flexible deployment
  • Comprehensive Logging: Detailed audit trails of all migration activities for troubleshooting and compliance

Business Impact

This system solves critical challenges for transportation departments and traffic management organizations:

  • Platform Flexibility: Freedom to choose the optimal database platform without losing historical data
  • Technology Migration: Smooth transition path for organizations upgrading their data infrastructure
  • Unified Analytics: Consistent reporting and dashboards regardless of the underlying database technology
  • Reduced Vendor Lock-in: Ability to migrate between open-source and commercial database solutions as needs evolve
  • Hybrid Deployments: Support for organizations maintaining multiple database platforms during transition periods

By providing a reliable migration path between database technologies, this solution gives organizations the flexibility to evolve their data architecture while preserving valuable traffic insights and historical analysis capabilities.

Technologies Used

PythonPython
Apache AirflowApache Airflow
dbtdbt
PostgreSQLPostgreSQL
MySQLMySQL
Apache SupersetApache Superset
RedashRedash
DockerDocker